Upgrading eigenspace-based prediction using null space and its application to path prediction

Proceedings of Subspace 2007 Page 17-23 published_at 2007-11
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Title ( eng )
Upgrading eigenspace-based prediction using null space and its application to path prediction
Creator
Shonomura Yuji
Amano Toshiyuki
Source Title
Proceedings of Subspace 2007
Start Page 17
End Page 23
Abstract
This paper proposes a method for an Eigenspace-based prediction of a vector with missing components by modifying a projection of conventional Eigenspace method, and demonstrates the application to the prediction of the path of a walking person. This modification is based on domain-specific knowledge of data, and a linear combination of vectors in the null space of Eigenspace is added so that a cost function of smoothness of path is minimized. Some experimental results on actual paths are shown to demonstrate how the proposed method works.
NDC
Electrical engineering [ 540 ]
Language
eng
Resource Type conference paper
Publisher
Asian Conference on Computer Vision
Date of Issued 2007-11
Rights
Copyright (c) 2007 by Author
Publish Type Version of Record
Access Rights open access
Source Identifier
[URI] http://ir.lib.hiroshima-u.ac.jp/00020422